language: en

[Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, 1995.]

Using Introspective Reasoning to Refine Indexing

Susan Fox and David B. Leake
Computer Science Department
Lindley Hall 215
Indiana University
Bloomington, IN 47405 USA
E-mail: fsfox,leakeg@cs.indiana.edu

Abstract Introspective reasoning about a system's own reasoning processes can form the basis for learning to refine those reasoning processes. The ROBBIE 1 system uses introspective reasoning to monitor the retrieval process of a case-based planner to detect retrieval of inappropriate cases. When retrieval problems are detected, the source of the problems is explained and the explanations are used to determine new indices to use during future case retrieval. The goal of ROBBIE's learning is to increase its ability to focus retrieval on relevant cases, with the aim of simultaneously decreasing the number of candidates to consider and increasing the likelihood that the system will be able to successfully adapt the retrieved cases to fit the current situation. We evaluate the benefits of the approach in light of empirical results examining the effects of index learning in the ROBBIE system.

1 Introduction